conftrace_
← Architectures
Deep Learning › Architectures ›

Neural Networks

11,723 papers

Papers per year

25
148
1385
860
'10
'15
'20
'25

Papers

On the Modularity of Hypernetworks NIPS 2020
Non-Euclidean Universal Approximation NIPS 2020
Sharp Representation Theorems for ReLU Networks with Precise Dependence on Depth NIPS 2020
Monotone operator equilibrium networks NIPS 2020
Object-Centric Learning with Slot Attention NIPS 2020
Deep Smoothing of the Implied Volatility Surface NIPS 2020
A shooting formulation of deep learning NIPS 2020
Counterexample-Guided Learning of Monotonic Neural Networks NIPS 2020
Temporal Spike Sequence Learning via Backpropagation for Deep Spiking Neural Networks NIPS 2020
Training Generative Adversarial Networks with Limited Data NIPS 2020
Deeply Learned Spectral Total Variation Decomposition NIPS 2020
Generative Neurosymbolic Machines NIPS 2020
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks NIPS 2020
The phase diagram of approximation rates for deep neural networks NIPS 2020
On Infinite-Width Hypernetworks NIPS 2020
The interplay between randomness and structure during learning in RNNs NIPS 2020
Convolutional Tensor-Train LSTM for Spatio-Temporal Learning NIPS 2020
Equivariant Networks for Hierarchical Structures NIPS 2020
Simplifying Hamiltonian and Lagrangian Neural Networks via Explicit Constraints NIPS 2020
Learning Deep Attribution Priors Based On Prior Knowledge NIPS 2020
Using noise to probe recurrent neural network structure and prune synapses NIPS 2020
Group Knowledge Transfer: Federated Learning of Large CNNs at the Edge NIPS 2020
Mutual exclusivity as a challenge for deep neural networks NIPS 2020
Rational neural networks NIPS 2020
STLnet: Signal Temporal Logic Enforced Multivariate Recurrent Neural Networks NIPS 2020